Results 101 to 110 of about 9,083 (186)

Global and Local Similarity Learning in Multi-Kernel Space for Nonnegative Matrix Factorization. [PDF]

Knowl Based Syst, 2023
Peng C, Hou X, Chen Y, Kang Z, Chen C, Cheng Q.   +5 more
europepmc   +1 more source

A review of decomposition methods for brain states estimation. [PDF]

Biomed Eng Online
Hu G, Wang J, Shui Z, Wang T, Wang D, Luo S, Liu H, Xie X, Nickerson LD.   +8 more
europepmc   +1 more source

Coupled nonnegative matrix/tensor factorization in brain imaging data

, 2020
Continuous advancement of brain imaging techniques has witnessed data analysis methods evolving from matrix component analysis to tensor component analysis, from individual analysis to group analysis regarding the analysis of brain data with multi-set/multi-modal, multi-coupling and multi-way characteristics.
openaire   +2 more sources

CTFacTomo: Reconstructing 3D spatial structures of RNA tomography transcriptomes by collapsed tensor factorization. [PDF]

PLoS Comput Biol
Song T, Nguyen Q, Broadbent C, Kuang R.
europepmc   +1 more source

Wasserstein Nonnegative Tensor Factorization with Manifold Regularization

Nonnegative tensor factorization (NTF) has become an important tool for feature extraction and part-based representation with preserved intrinsic structure information from nonnegative high-order data. However, the original NTF methods utilize Euclidean or Kullback-Leibler divergence as the loss function which treats each feature equally leading to the
Wang, Jianyu, Tang, Linruize
openaire   +1 more source

Robust self supervised symmetric nonnegative matrix factorization to the graph clustering. [PDF]

Sci Rep
Ru Y, Gruninger M, Dou Y.
europepmc   +1 more source

Deciphering high-order structures in spatial transcriptomes with graph-guided Tucker decomposition. [PDF]

Bioinformatics
Broadbent C, Song T, Kuang R.
europepmc   +1 more source

A New Method for Dynamic Brain Connectivity Analysis Based on Tensor Decomposition in Tinnitus Using High-density Electroencephalogram in Source Domain. [PDF]

J Med Signals Sens
Bahman M, Sajadi SS, Toostani IG, MakkiAbadi B.   +3 more
europepmc   +1 more source

The structure is the message: Preserving experimental context through tensor decomposition. [PDF]

Cell Syst
Tan ZC, Meyer AS.
europepmc   +1 more source

From biogenesis to deep modeling: a holistic review of miRNA-disease prediction computational methods with experimental comparison. [PDF]

Brief Bioinform
Xie S, Law KLE.
europepmc   +1 more source